Robust platform for inline Raman monitoring and control of perfusion cell culture

Abstract

AbstractPerfusion cell culture has been gaining increasing popularity for biologics manufacturing due to benefits such as smaller footprint, increased productivity, consistent product quality and manufacturing flexibility, cost savings, and so forth. Process Analytics Technologies tools are highly desirable for effective monitoring and control of long‐running perfusion processes. Raman has been widely investigated for monitoring and control of traditional fed batch cell culture process. However, implementation of Raman for perfusion cell culture has been very limited mainly due to challenges with high‐cell density and long running times during perfusion which cause extremely high fluorescence interference to Raman spectra and consequently it is exceedingly difficult to develop robust chemometrics models. In this work, a platform based on Raman measurement of permeate has been proposed for effective analysis of perfusion process. It has been demonstrated that this platform can effectively circumvent the fluorescence interference issue while providing rich and timely information about perfusion dynamics to enable efficient process monitoring and robust bioreactor feed control. With the highly consistent spectral data from cell‐free sample matrix, development of chemometrics models can be greatly facilitated. Based on this platform, Raman models have been developed for good measurement of several analytes including glucose, lactate, glutamine, glutamate, and permeate titer. Performance of Raman models developed this way has been systematically evaluated and the models have shown good robustness against changes in perfusion scale and variations in permeate flowrate; thus models developed from small lab scale can be directly transferred for implementation in much larger scale of perfusion. With demonstrated robustness, this platform provides a reliable approach for automated glucose feed control in perfusion bioreactors. Glucose model developed from small lab scale has been successfully implemented for automated continuous glucose feed control of perfusion cell culture at much larger scale.